Qualitative Researcher MCP Server

An MCP server implementation that provides tools for managing qualitative research knowledge graphs, enabling structured representation of research projects, participants, interviews, observations, codes, themes, and findings. This server helps qualitative researchers organize their data, track their analysis process, develop themes, and generate insights from rich textual data.

Features

Persistent Research Context: Maintain a structured knowledge graph of research entities and relationships across multiple analysis sessions
Study Session Management: Track research analysis sessions with unique IDs and record progress over time
Thematic Analysis: Organize and track emergent themes across data sources
Coding Framework: Manage hierarchical coding structures and track code applications
Participant Management: Track participant data, demographics, and contributions
Data Source Organization: Organize interviews, observations, and documents
Research Question Tracking: Link data to specific research questions
Memo Writing: Document analytical insights throughout the research process
Chronological Data Analysis: Explore data in temporal sequence
Code Co-occurrence Analysis: Identify relationships between different codes
Methodology Documentation: Track methodological decisions and approaches

Entities

The Qualitative Researcher MCP Server recognizes the following entity types:

project: Overall research study
participant: Research subjects
interview: Formal conversation with participants
observation: Field notes from observational research
document: External materials being analyzed
code: Labels applied to data segments
codeGroup: Categories or families of related codes
memo: Researcher's analytical notes
theme: Emergent patterns across data
quote: Notable excerpts from data sources
literature: Academic sources
researchQuestion: Formal questions guiding the study
finding: Results or conclusions
status: Entity status values (active, completed, pending, abandoned)
priority: Priority level values (high, low)

Relationships

Entities can be connected through the following relationship types:

participated_in: Links participants to interviews/observations
codes: Shows which codes apply to which data
contains: Hierarchical relationship (e.g., codegroup contains codes)
supports: Data supporting a theme or finding
contradicts: Data contradicting a theme or finding
answers: Data addressing a research question
cites: References to literature
followed_by: Temporal sequence
related_to: General connection
reflects_on: Memo reflecting on data/code/theme
compares: Comparative relationship
conducted_by: Person who conducted data collection
transcribed_by: Person who transcribed data
part_of: Entity is part of another entity
derived_from: Entity is derived from another entity
collected_on: Data collection date
analyzes: Analysis relationship
triangulates_with: Triangulation between data sources
has_status: Links entities to their current status (active, completed, pending, abandoned)
has_priority: Links entities to their priority level (high, low)
precedes: Indicates that one analysis activity comes before another in a sequence

Available Tools

The Qualitative Researcher MCP Server provides these tools for interacting with research knowledge:

startsession

Starts a new qualitative research session, generating a unique session ID and displaying current research projects, recent data collection, emergent themes, and previous sessions. Shows status information via has_status relations, priority levels via has_priority relations, and identifies research activities ready to be worked on next based on sequential process relationships.

loadcontext

Loads detailed context for a specific entity (project, participant, interview, etc.), displaying relevant information based on entity type. Includes status information, priority levels, and sequential process relationships.

endsession

Records the results of a research session through a structured, multi-stage process:

summary: Records session summary, duration, and project focus
interviewData: Documents new interview data processed during the session
memos: Records analytical memos created during the session
codingActivity: Tracks new and revised codes applied to data
themes: Documents emergent or developed themes from analysis
statusUpdates: Records changes to entity status values
projectStatus: Updates overall project status, priority assignments, and sequential relationships
assembly: Final assembly of all session data

buildcontext

Creates new entities, relations, or observations in the knowledge graph:

entities: Add new research entities (projects, participants, interviews, status, priority, etc.)
relations: Create relationships between entities (including has_status, has_priority, precedes)
observations: Add observations to existing entities

deletecontext

Removes entities, relations, or observations from the knowledge graph:

entities: Remove research entities
relations: Remove relationships between entities (including status, priority, and sequential relations)
observations: Remove specific observations from entities

advancedcontext

Retrieves information from the knowledge graph:

graph: Get the entire knowledge graph
search: Search for nodes based on query criteria
nodes: Get specific nodes by name
related: Find related entities
status: Find entities with a specific status value (active, completed, pending, abandoned)
priority: Find entities with a specific priority value (high, low)
sequence: Identify sequential relationships for analysis activities

Domain-Specific Functions

The Qualitative Researcher MCP Server includes specialized domain functions for qualitative research:

getProjectOverview: Comprehensive view of a project including research questions, methodology, participants, data sources
getParticipantProfile: Detailed profile of a participant including demographics, interviews, and quotes
getThematicAnalysis: Analysis of themes with supporting codes and data
getCodedData: View all data segments tagged with a specific code
getResearchQuestionAnalysis: Organize data by research questions with related findings
getChronologicalData: View data in temporal sequence
getCodeCooccurrence: Analyze where multiple codes appear together
getMemosByFocus: Retrieve all memos related to a specific entity
getMethodologyDetails: Review methodological approach, sampling, and analysis techniques
getRelatedEntities: Find entities related to a specific entity by relationship type
getStatusOverview: View all entities with a specific status (active, completed, pending, abandoned)
getPriorityItems: Identify high-priority research tasks and activities
getAnalysisSequence: Visualize the sequence of analysis activities based on precedes relations

Example Prompts

Starting a Session

Let's start a new qualitative research session for my Health Behavior Study project.

Loading Research Context

Load the context for the Health Behavior Study project so I can see the current state of my analysis.

Recording Session Results

I've just finished analyzing interview data for my Health Behavior Study. I identified two new themes related to social support, coded three new interviews, and wrote memos about emerging patterns in participant responses. I've marked the initial coding phase as complete and set the thematic analysis as high priority. The project is progressing well, and I'm beginning to reach theoretical saturation.

Managing Research Knowledge

Create a new code called "Family Support" that's part of the "Social Support" code group in the Health Behavior Study project. Set its status to active and make it precede the "Social Network Analysis" activity.

Update the status of the "Participant Recruitment" process to "completed" and add an observation that we've reached our target sample size.

Usage

This MCP server enables qualitative researchers to:

Maintain Analytical Continuity: Keep track of analysis progress across multiple research sessions
Develop Coding Frameworks: Build, refine, and apply coding structures to qualitative data
Track Thematic Development: Observe how themes emerge and evolve during analysis
Manage Rich Data Sources: Organize and connect interview transcripts, field notes, and documents
Support Theoretical Development: Document theoretical insights through the memo writing process
Prepare Research Findings: Connect findings to supporting evidence and research questions
Enhance Methodological Rigor: Document methodological decisions and analysis process
Track Research Progress: Monitor entity status throughout the research lifecycle
Prioritize Research Tasks: Identify and focus on high-priority research activities
Sequence Analysis Activities: Plan and visualize the logical order of research and analytical steps

Configuration

Usage with Claude Desktop

Add this to your claude_desktop_config.json:

Install from GitHub and run with npx

{
  "mcpServers": {
    "qualitativeresearch": {
      "command": "npx",
      "args": [
        "-y",
        "github:tejpalvirk/qualitativeresearch"
      ]
    }
  }
}

Install globally and run directly

First, install the package globally:

npm install -g github:tejpalvirk/qualitativeresearch

Then configure Claude Desktop:

{
  "mcpServers": {
    "qualitativeresearch": {
      "command": "contextmanager-qualitativeresearch"
    }
  }
}

docker

{
  "mcpServers": {
    "qualitativeresearch": {
      "command": "docker",
      "args": [
        "run",
        "--rm",
        "-i",
        "mcp/qualitativeresearch"
      ]
    }
  }
}

Building

From Source

# Clone the repository
git clone https://github.com/tejpalvirk/contextmanager.git
cd contextmanager

# Install dependencies
npm install

# Build the server
npm run build

# Run the server
cd qualitativeresearch
node qualitativeresearch_index.js

Docker:

docker build -t mcp/qualitativeresearch -f qualitativeresearch/Dockerfile .

License

This MCP server is licensed under the MIT License. This means you are free to use, modify, and distribute the software, subject to the terms and conditions of the MIT License. For more details, please see the LICENSE file in the project repository.

Environment Variables

The Qualitative Research MCP Server supports the following environment variables to customize where data is stored:

MEMORY_FILE_PATH: Path where the knowledge graph data will be stored
- Can be absolute or relative (relative paths use current working directory)
- Default: ./qualitativeresearch/memory.json
SESSIONS_FILE_PATH: Path where session data will be stored
- Can be absolute or relative (relative paths use current working directory)
- Default: ./qualitativeresearch/sessions.json

Example usage:

# Store data in the current directory
MEMORY_FILE_PATH="./qualitative-memory.json" SESSIONS_FILE_PATH="./qualitative-sessions.json" npx github:tejpalvirk/contextmanager-qualitativeresearch

# Store data in a specific location (absolute path)
MEMORY_FILE_PATH="/path/to/data/qualitative-memory.json" npx github:tejpalvirk/contextmanager-qualitativeresearch

# Store data in user's home directory
MEMORY_FILE_PATH="$HOME/contextmanager/qualitative-memory.json" npx github:tejpalvirk/contextmanager-qualitativeresearch

Qualitative Researcher MCP Server

Integrations

Qualitative Researcher MCP Server

Features

Entities

Relationships

Available Tools

startsession

loadcontext

endsession

buildcontext

deletecontext

advancedcontext

Domain-Specific Functions

Example Prompts

Starting a Session

Loading Research Context

Recording Session Results

Managing Research Knowledge

Usage

Configuration

Usage with Claude Desktop

Install from GitHub and run with npx

Install globally and run directly

docker

Building

From Source

Docker:

License

Environment Variables

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